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qwen3-8b-mgsm-dsam-ca – AI Model by xummer | AlphaNeural AI
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qwen3-8b-mgsm-dsam-ca
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ca
This model is a fine-tuned version of
Qwen/Qwen3-8B
on the mgsm_ca_train dataset. It achieves the following results on the evaluation set:
Loss: 0.4874
Accuracy: 0.8681
Mcq Accuracy: 0.1538
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0002
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 5.0
Training results
Framework versions
PEFT 0.18.1
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
